Data Scientist

Stacy Shingleton

Houston TX, ***** 281-***-**** ***************@*****.*** GitHub Medium LinkedIn Data Scientist

Experience in data acquisition and data modeling, statistical analysis, machine learning, deep learning, and NLP. With over five years industry experience in specialty polymer research and development, I bring strong skills in problem solving and project management, and possess proven communication skills with team members and customers. TECHNICAL SKILLS

Python, SQL, scikit-learn, NumPy, pandas, seaborn, matplotlib, Beautiful Soup (web scraping), Surprise, Machine Learning Models

(Classification and Regression), Statistical Analysis, API Calls, NoSQL (MongoDB), Docker, Git, Spark, PySpark, OSEMN, AWS, JSON, CRISP-DM, Data Mining

TECHNICAL PROJECTS

Building a Regression Model - Github

Built a regressor to predict lifetime box office gross to assist investors and production companies in budgeting movies

● Scraped three HTML sites using the Python library Beautiful Soup

● Converted scraped data to data frames using JSON and pandas

● Cleaned and converted categorical data to binary data using various encoding methods such as MultiLabelBinarizer

● Completed exploratory data analysis on regression data using pandas and seaborn

● Built and scored a variety of regressors with feature importance plots Building a Classification Model - Github

Built a classifier to predict flight delays for airlines to reduce operational costs and emissions

● Imported and filtered a raw dataset that contained information on 5.8 million flights

● Completed an API call to collect hourly weather data which was then joined onto the flights dataset

● Cleaned and converted categorical data to binary data using various encoding methods such as OneHotEncoder

● Completed exploratory data analysis on classification data using pandas and seaborn

● Built and scored a variety of classifier models with feature importance plots and confusion matrices Building a Recommendation System - Github

Built a recommendation system that provides a list of recommended movies for new users

● Extracted and joined datasets containing user reviews and movie titles

● Cleaned and completed exploratory data analysis using pandas and seaborn

● Built a recommendation system using python SciKit Surprise which provides new users with movie recommendations Hypothesis Testing with SQL - Github

Completed hypothesis testing using statistical analysis to provide valuable sales and marketing insights for a grocery provider

● Explored an Entity Relationship Diagram (ERD)

● Created functions to calculate the t-statistic, degrees of freedom, and p-value for a Welch’s t-test

● Completed numerous SQL queries to obtain the necessary data from the ERD for statistical analysis

● Completed Welch’s t-test on data distributions to either reject or fail to reject various null hypotheses EMPLOYMENT HISTORY

Senior Technical Associate, Kraton Corporation, Houston, TX 01/2014 - 12/2019

● Designed and built the first pressurized polymerization reactor at the Kraton Innovation Center

● Oversaw a capital project with a team of six colleagues and managed a 100K budget while meeting deadlines

● Worked directly with customers developing novel polymers for new business developments

● Organized and presented annual sitewide OSHA safety trainings to over 50 employees

● Certified Lean Six Sigma Yellow Belt

EDUCATION

Flatiron School, Online 01/2020 - 06/2020

Immersive Data Science Bootcamp program

The University of Texas, Austin, TX 08/2009 - 12/2013 Bachelor of Science in Chemistry

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